Triple
T19067313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welcome, Georgia |
E466698
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Welcome |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Welcome | Statement: [Welcome, Georgia, hasName, Welcome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Welcome Context triple: [Welcome, Georgia, hasName, Welcome]
-
A.
Welcome
chosen
Welcome is an unincorporated rural community located in Coweta County, Georgia, United States.
-
B.
Welcome
"Welcome" is a 1973 jazz fusion–oriented studio album by the Latin rock band Santana, noted for its spiritual themes and experimental, progressive sound.
-
C.
Welcome
"Welcome" is a song best known for being part of the Back to Basics Tour setlist.
-
D.
Welcome
"Welcome" is a popular 2007 Indian Bollywood comedy film known for its ensemble cast, slapstick humor, and memorable comic sequences.
-
E.
Welcome
Welcome is a 2009 French drama film directed by Philippe Lioret, known for its poignant portrayal of an Iraqi Kurdish refugee in Calais who trains to swim the English Channel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19918848190abb6dd060a9dbecb |
completed | April 20, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:03 p.m.